Engineers pumped up about biomechanics of riding bikes

UC Davis mechanical and aerospace engineers aren’t just reinventing the wheel. They hope to reinvent the whole bike with new designs that make it easier to ride for balance-challenged folks.

"We'd like to know what makes a bicycle hard to ride, and can we make it easier," said Mont Hubbard, a co-investigator with fellow professor Ron Hess in the Department of Mechanical and Aerospace Engineering. The researchers hope to look at how different populations — such as seniors — ride, and whether bicycle designs could be tailored to their needs.

First, they must understand how a human controls a bicycle — in some ways more challenging than understanding how a pilot flies an airplane.

"There's a lot of folklore and experience, but we don't have a precise scientific understanding of how humans control bicycles," said Hubbard, who leads the Sports Biomechanics Laboratory.

Hess, a nationally recognized expert on how pilots interact with aircraft control systems, said that riding a bike turns out to be a more complex problem.

"What makes riding a bicycle unique is that you have to use all the sensory information available," he said. That includes not just one’s visual system (the eyes) but also systems that sense angular motion (vestibular sensors in the inner ear), and others that provide information regarding limb movement (proprioceptive sensors in the arms and legs).

For example, Hess said, it is possible to build a flight or driving simulator without motion cues. Bicycle simulators should offer the sensation of “leaning” to be realistic.

The research group includes graduate students Jason Moore, Dale Peterson, Danique Fintelman, Peter de Lange, Chris Dembia, Gilbert Gede and undergraduates Derek Pell, Joseph Rinek, Eric Chan, Steve Brendel, Chet Corcos, Aurelia Darling, Mohammad Osman and Steven Yen.

The team is building bicycles fitted with sensors to measure precisely how the vehicle and the rider move. They will capture motion on video and analyze it with computer models.

They are also building a robot bicycle based on their findings, Hess said.

Their study is being supported by a two-year, $300,000 grant from the National Science Foundation that began in November 2009.

This story was updated from a May 20, 2010, story written by Andy Fell of the UC Davis News Service.
 

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Susanne Rockwell, Web and new media editor, (530) 752-2542, sgrockwell@ucdavis.edu

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